Containerized desalination system

ABSTRACT

A water desalination system includes a first set of ultrafiltration membranes, a second set of ultrafiltration membranes, a first backwashing system configured to treat at least one of the first set of ultrafiltration membranes or the second set of ultrafiltration membranes with brine generated by a reverse osmosis process, and a second backwashing system configured to treat at least one of the first set of ultrafiltration membranes or the second set of ultrafiltration membranes with one or more chemicals and reverse osmosis permeate water.

PRIORITY CLAIM

This application is a divisional of U.S. patent application Ser. No.15/772,808 filed May 1, 2018 (now U.S. Pat. No. 10,836,656), which is aU.S. National Stage Filing under 35 U.S.C. 371 from InternationalApplication No. PCT/US2017/051842 filed Sep. 15, 2017 and published asPCT/US2017/051842 on Mar. 22, 2018, which is related to and claims thebenefit of priority to U.S. Patent Application No. 62/395,317, filedSep. 15, 2016, which applications and publications are incorporatedherein by reference in their entirety.

TECHNICAL FIELD

Aspects and implementations of the present disclosure relate to waterdesalination systems.

BACKGROUND

Water desalination is a process that extracts minerals from salinewater. Various desalination methods can be employed such as reverseosmosis.

BRIEF DESCRIPTION OF THE DRAWINGS

Aspects and implementations of the present disclosure will be understoodmore fully from the detailed description given below and from theaccompanying drawings of various aspects and implementations of thedisclosure, which, however, should not be taken to limit the disclosureto the specific aspects or implementations, but are for explanation andunderstanding only.

FIG. 1 illustrates an example system, in accordance with an exampleembodiment.

FIG. 2 illustrates an example system, in accordance with an exampleembodiment.

FIG. 3 illustrates an example system, in accordance with an exampleembodiment.

FIG. 4 is a flow chart illustrating a method, in accordance with anexample embodiment described herein.

FIG. 5 illustrates an example scenario described herein, according to anexample embodiment.

FIG. 6 illustrates an example scenario described herein, according to anexample embodiment.

FIG. 7 is a block diagram illustrating components of a machine able toread instructions from a machine-readable medium and perform variousmethodologies discussed herein, according to an example embodiment.

DETAILED DESCRIPTION

Aspects and implementations of the present disclosure are directed towater desalination and desalination systems. As described in detailherein, the disclosed technologies may be implemented in a single,standalone container (e.g., a complete plant, mounted in a 40-foottemperature controlled container), while in other implementations thedescribed technologies may be configured differently and/or distributedacross multiple containers, structures, etc. It should be understoodthat a single container may allow quick installation and easy operationof the technologies, providing a solution for seawater desalination withlow energy and/or chemical consumption.

In certain implementations, the described technologies include orotherwise incorporate a pretreatment system, as described herein. Such apretreatment system may include one or more disc filters (DF) and/orultra-filtration (UF) membranes. In doing so, continuous operation canbe ensured (e.g., at raw water quality up to 20 Nephelometric TurbidityUnits (NTU)).

Additionally, in certain implementations the described technologies canbe configured to utilize reverse osmosis (RO) brine for backwash, e.g.,of the UF membranes. In doing so, recovery can be increased and savingson backwash equipment can be realized.

Moreover, in certain implementations high flux/low energy reverseosmosis membranes can be utilized. Such membranes are used to removedissolved solids in seawater by the mechanical process which reversesand overcomes the osmotic pressure of sea water by passing water throughthe membranes while salts are retained. In doing so, operating pressurecan be reduced energy savings can be realized.

In certain implementations, the described technologies can be configuredto enable direct feeding from UF to RO. In doing so, the need for anintermediate tank, cartridge filter and/or low-pressure pump (as inexisting systems) can be eliminated, thereby reducing operating costs &footprint of the system.

Additionally, in certain implementations the described technologies caninclude one or more efficient piston high-pressure pump(s) and/oradvanced energy recovery device(s) (ERD) 112. In doing so, significantamounts of energy costs can be reduced, as compared to units without(ERD). Such an ERD can utilize isobaric chambers technology, and canmaximize energy efficiency of the seawater RO, by recovering theresidual pressure (energy) contained in the brine rejection andtransferring it to the RO feed water. The brine is collected anddirected to the ERD and its pressure is mechanically transferred is to aportion of the incoming feed water from the intake. Because of frictionlosses and differential pressure (ΔP) of the membranes, a booster pumpin series with the ERD, can be used to align with the pressure of theremaining feed the pump intake system. Additionally, in certainimplementations the referenced ERD can include a pressure exchangerintegrated with and booster pump and an electric motor.

The described technologies can also enable lower levels of chemicalconsumption (as compared to existing systems). For example, in certainimplementations the osmotic differential pressure in the backwash (BW)and chemical enhanced backwash (CEB) of the UF can be used to achieve abiocide effect (thereby reducing chemical consumption in the system).

Additionally, in certain implementations the pumps of the describedsystem can be equipped with variable frequency drive (VFD). In doing so,a wide/flexible operating range can be achieved.

The described technologies can also be configured to operate in a fullyautomatic manner, with high availability and low maintenance, asdescribed herein.

FIG. 1 depicts one exemplary embodiment of the described system 100(further aspects of the system are also shown in FIGS. 2 and 3 ). Incertain implementations, system 100 includes a disc filter system forretention of suspended solids (e.g., up to 130 microns), e.g., during apretreatment process. For example, as shown in FIG. 3 , water such asraw water 302 can be received by system 100 and provided to disc filtersystem 304 which can include one or several disc filters 305. Such discfilters 305 can be designed or configured for coarse filtration (e.g.,prior to providing the water to UF membranes). The disc filtrationsystem 302 can capture and retain large quantities of solid particles,such as organic solids & algae.

As turbid water 302 flows through the filter(s) 305, waste can becaptured in the outer wall and/or the inner grooves of a stack ofcompressed discs. During an automatic cleaning cycle, the pack can bedecompressed, while a series of nozzles direct streams of water at highpressure between the disks, causing the disks to spin and rinse. At theend of the backwash cycle, the discs pack can be recompressed and thesystem returns to the filtration cycle. The system is thus fullyautomatic, self-cleaning, corrosion resistant, easy to operate andmaintain. It should be understood that system 100 can be configured toprovide the necessary flow of filtered water to the UF feed even duringbackwash operations.

The system also includes an ultrafiltration (UF) system 306 forretention of suspended solids, as shown in FIG. 3 . Utilizing such a UFsystem can ensure, for example, levels of 0.2 NTU turbidity and SDI lessthan 2.5, thus providing effective protection for the reverse osmosismembranes. The UF system can include ultrafiltration (UF) membrane(s) toremove fine particulate matter. This technology is used in watertreatment, and as a pretreatment process to feed the reverse osmosismembranes. Compared with multimedia filters, ultrafiltration technologyhas the advantage of its ability to eliminate germs, microorganisms,etc. from water. The pores of such membrane(s) can be small enough toeven prevent viruses passing through them (e.g., about 20 nm).

In certain implementations, system 100 can include a control system 114.Such a control system can be or include a programmable logic controller(PLC) and/or another computing device (or devices) configured tocommunicate with the various components described herein. Control system114 can control and/or configure system 100 in accordance with variousoperations, processes, etc., such as modes of the ultrafiltrationprocess including but not limited to filtration, backwashing and CEB.

FIG. 4 is a flow chart illustrating a method 400, according to anexample embodiment, for containerized desalination system backwashing.The method is performed by the various components described herein, suchas in system 100. In other implementations, the one or more blocks ofFIG. 4 can be performed by another machine or machines.

For simplicity of explanation, methods are depicted and described as aseries of acts. However, acts in accordance with this disclosure canoccur in various orders and/or concurrently, and with other acts notpresented and described herein. Furthermore, not all illustrated actsmay be required to implement the methods in accordance with thedisclosed subject matter. In addition, those skilled in the art willunderstand and appreciate that the methods could alternatively berepresented as a series of interrelated states via a state diagram orevents.

At operation 410, water is passed through a reverse osmosis process,e.g., as described herein. At operation 420, a first set ofultrafiltration membranes or a second set of ultrafiltration membranescan be backwashed, e.g., with brine generated by the reverse osmosisprocess. At operation 430, at least one of the first set ofultrafiltration membranes or the second set of ultrafiltration membranescan be backwashed with one or more chemicals and reverse osmosispermeate, e.g., as described herein. Further aspects of the referencedmethod are described in detail herein.

System 100 can also include a UF backwash system 102. In certainimplementations, the backwash system can perform backwashes using RObrine, as described herein. In doing so, the total recovery of thesystem can be increased and energy can be saved. Additionally, system100 can be configured to use brine from the RO process to perform the UFbackwash, e.g., with a direct feed, using the residual pressure in thebrine flow. In doing so, the need for a pump for this specific functioncan be eliminated, and energy can be saved. As a further advantage, theuse of brine in such processes inhibits the growth of microorganisms onthe surface of the UF membrane, as a disinfecting effect is provided bythe difference between the osmotic potential between seawater and brine.

Additionally, as noted, in certain implementations UF membranes are usedfor pre-treatment of the water prior to feeding the water into thedesalination stage. In certain implementations, the UF membranes can becleaned periodically using water backwash to remove solids and foulingthat accumulate on the membrane. In lieu of backwashing using UFpermeate water (as in existing systems), the described technologies canbe configured to enable a backwashing using brine, e.g., from thedesalination stage. Since RO brine is a ‘waste’ stream’, its use as thebackwash saves valuable UF permeate and therefore increases the overallsystem's recovery & efficiency. The brine can be pressurized and its usefor UF backwash can eliminate the need for special equipment thatotherwise would be required to perform the backwash (e.g., tank &pumps). This contributes to space, energy & cost saving. Additionally,the high salinity in the brine can also prevent/eliminate biologicalfouling on the UF membranes due its high salinity that periodicallycreates ‘osmotic shock’ that does not allow bacteria to proliferate.This can contribute to reduction in chemical disinfection of the UFmembrane thus saves chemical costs and reduces environmental impact.

Moreover, in certain implementations the described technologies caninclude UF configuration at multiple (e.g., 4) independent trains 106 ofUF membranes. By way of further illustration, as shown in FIG. 3 , UFsystem 306 can include UF train 308A and UF train 308B (as well as otherUF trains). Such a configuration allows direct continuous feed ofseawater reverse osmosis (SWRO) permeate. Additionally, such aconfiguration can enable continuous operation of the RO even during UFbackwash (BW) and chemical enhanced backwash (CEB) processes (asdescribed herein). In certain implementations, the describedconfiguration can enable such BW and CEB processes to be performed evenwithout an intermediate tank, RO feed pump and/or safety cartridgefilter. Such a configuration can reduce the footprint of the system,equipment cost & energy use by the system.

As noted above, system 100 can include a control system 114. In certainimplementations, control system 114 can synchronize or otherwise monitorand/or adjust the operation of the referenced UF trains (and/or othercomponents described herein). For example, by synchronizing operation ofthe referenced trains, in a scenario in which one train is undergoing acleaning process (e.g., BW, CEB, etc., as described herein) othertrain(s) can remain in operation. In doing so, RO operation of thesystem 100 can remain stable/consistent. In certain implementations, thefeed water pressure can be supplied by the raw water feed pump (e.g.,302) directly through the pre-filtration stages into the RO.

Additionally, in certain implementations the system 100 can includetank/air compressor 110. Such a tank/compressor 110 can be configured toutilize compressed air during the UF backwashing (e.g., in lieu of ablower).

The system 100 can also include a chemical enhanced backwash (CEB)system 104. In certain implementations, the UF elements (CEB) can becleaned using RO permeate. In doing so, the amount of chemicals used(e.g., NaOCl and HCl) can be significantly reduced (as compared toexisting systems). The system may be configured to perform the chemicalcleaning automatically (e.g., once every 24 hours or at otherintervals). Doing so can, for example, prevent biological contaminationon UF membranes of UF system 306. In certain implementations, such anautomatic chemical enhanced backwash process can be performed on UFmembrane(s) in order to prevent biofilm and scale formation on themembranes surface.

In certain implementations, CEB system 104 can use the RO permeate waterin conjunction with has various chemical dosing systems (e.g., for 35%HCl and 10% NaOCl solutions). For example, FIG. 3 depicts various dosingsystems within CEB system 104. As shown in FIG. 3 , dosing system 310Acan be a dosing system for NaOCl, while dosing system 310B can be adosing system for HCl. In certain implementations, each of thereferenced dosing system(s) can include a dosing pump 312, a tank (e.g.,a High-density polyethylene (HDPE) tank), valve(s) 316 (e.g.,anti-siphon valves) and/or a spill containment bund.

By way of further illustration, it can be appreciated that indesalination systems, the UF membranes may need to be cleanedperiodically, e.g., by chemicals that are dosed into the backwash water(CEB). In many cases CEB is done with same water as the water backwash(i.e., saline UF permeate). In the described technologies, such as insystem 100, the use of desalinated water (RO permeate) instead ofseawater for CEB can significantly reduce the quantity of chemicalsrequired to reach the desirable pH for the caustic CEB operation, duethe elimination of the buffering effect caused by the seawater'salkalinity & dissolved salts. In certain implementations, the describedtechnologies can utilize a direct connection from the RO permeate intothe UF backwash system with chemicals dosing into the permeate line,e.g., as shown in FIG. 3 .

In addition, the use of the low salinity water (RO permeate) for CEB,further in combination of high salinity RO brine for backwash, resultsin high ‘osmotic shock’. This contributes to prevention of biofilmformation at the UF membranes, due to ‘osmotic shock’ and also furtherreduces the required quantity of chlorine application during the CEBoperation.

In certain implementations, the system can include an anti-oxidant(e.g., sodium metabisulfite—‘SMBS’) dosing system 310C. Such a dosingsystem can be used in the manner described herein to prevent oxidationof the RO membranes. Additionally, a scale inhibitor (anti-scaling)dosing system can be used in the manner described herein to preventaccumulation of salt (scaling), e.g., in reverse osmosis membranes.

A high pressure pumping system 316 can be configured with respect to theRO membranes 318. In certain implementations, such a system may includea piston pump and energy recovery device 112 by isobaric pressureexchanger type conjugated with a booster pump 320.

Additionally, in certain implementations the described RO system mayinclude fiberglass (FRP) pressure vessels and high flux/ultra-lowpressure seawater reverse osmosis (SWRO) membranes. For example, incertain implementations system 100 can be configured with 8 pressurevessels for 6 elements, with a multiport system that eliminates the needfor interconnections. The pressure vessels can be designed for anoperating pressure greater than 1000 psi (69 bar).

In certain implementations, system 100 can also include a flush andclean in place (CIP) system 330. Such a CIP system 330 can be configuredto perform rinsing operations automatically, e.g., in scenarios in whichthe RO system is stopped for a defined period of time (e.g., more than15 minutes). Additionally, the referenced rinsing and CIP unit can beconfigured for periodic deep cleaning of RO/UF membranes. In certainimplementations, CIP system 330 can include a tank 332 (e.g., a 2,500liter PP tank with 25 kW heater), a centrifugal pump 334 with anelectric motor and variable frequency drive (VFD), and a disk filter.

Moreover, in certain implementations a potabilization system can beincluded. For example, if the desalinated water is used for drinking,system 100 can be equipped with an optional Na₂CO₃ chemicals dosingand/or calcite filters to restore hardness to desired/required levels,and to adjust the pH, as well as dosage of sodium hypochlorite (NaOCl)to prevent drinking water biological re-contamination.

Various analytical instruments, sensors, etc. can also be included insystem 100. Such instruments, sensors, etc. can, for example, enableremote devices, transmitters, etc. to control the flow, pressure, pH,conductivity, and temperature at various points, e.g., as describedherein. Additionally, such sensors, instruments, etc., can be connectedto and/or otherwise configured in relation to control system 114.

Moreover, in certain implementations various additional components canbe included and/or otherwise incorporated/integrated into system 100,including but not limited to: a beach well intake pumping system, apumping system for seawater from the raw water tank, a multimediafilter, re-mineralization by injection of sodium bicarbonate and calciumchloride solution, re-mineralization by calcite (CaCO3) filters system,post-chlorination by injection of sodium hypochlorite (NaOCl), permeatepolisher by RO second pass, and/or permeate polisher by CEDI.

In certain implementations, system 100 can also include a vertical discfilter battery 108, which can also serve to reduce the footprint of thesystem, as shown.

Accordingly, described herein is water desalination system. In variousimplementations the system includes a first set of ultrafiltrationmembranes, a second set of ultrafiltration membranes, a firstbackwashing system configured to treat at least one of the first set ofultrafiltration membranes or the second set of ultrafiltration membraneswith brine generated by a reverse osmosis process, and a secondbackwashing system configured to treat at least one of the first set ofultrafiltration membranes or the second set of ultrafiltration membraneswith one or more chemicals and reverse osmosis permeate water.

Implementing the described technologies can provide substantial benefitsand advantages. For example, the described technologies can adjust,improve, and/or optimize operation of the described system(s) (e.g.,desalination units, plants, etc.). Doing so can achieve efficienciesand/or savings, e.g., through optimization of various operations andmaintenance cost factors. For example, as described herein, thedescribed technologies can improve/optimize hardware maintenance (byincreasing service life of the hardware), chemical consumption, energyconsumption (by optimizing/improving flow rates and process parameters,and of the recovery for brackish water plants), manpower and/or plantavailability. In addition, improving plant availability and reliabilitycan further reduce the need for various design safety factors and canlower equipment redundancy thus further preserving resources.

As described herein, smart operations engine can be configured tocollect, generate, and/or provide sophisticated automatic diagnosticsand performance reports, e.g., based on the data collected from amonitoring system (e.g., control system 114 as described above). Forexample, FIG. 5 depicts an example server 502 that executes or otherwiseimplements smart operations engine 504 (which can be an application,module, etc., executing on server 502 and/or any other such computingdevice(s)). Server 502 can be connected to and/or communicate withvarious plants, sites, etc., e.g., via a network 510 (e.g., theInternet) as shown in FIG. 5 . Upon analyzing or otherwise processingsuch data, smart operations engine can generate and/or otherwiseimplement various adjustments, e.g., to maximize the operation of theplant. Doing so enables real-time analysis of the plant performance, andcan identify latent performance issues, performance degradation, and/orother inefficiencies. Additionally, having identified such phenomena,smart operations engine can generate and/or provide variousrecommendations, corrective measures and/or performance optimizationadjustments.

In certain implementations, the described techniques can be employed asmethods, such as may be performed by processing logic that can comprisehardware (circuitry, dedicated logic, etc.), software (such as is run ona computing device such as those described herein), or a combination ofboth. In one implementation, these methods 400 is performed by one ormore elements depicted and/or described in relation to FIG. 1 (includingbut not limited to control system 114), while in some otherimplementations, the operations can be performed by another machine ormachines (e.g., server 502).

For simplicity of explanation, methods are depicted and described as aseries of acts. However, acts in accordance with this disclosure canoccur in various orders and/or concurrently, and with other acts notpresented and described herein. Furthermore, not all illustrated actsmay be required to implement the methods in accordance with thedisclosed subject matter. In addition, those skilled in the art willunderstand and appreciate that the methods could alternatively berepresented as a series of interrelated states via a state diagram orevents. Additionally, it should be appreciated that the methodsdisclosed in this specification are capable of being stored on anarticle of manufacture to facilitate transporting and transferring suchmethods to computing devices. The term article of manufacture, as usedherein, is intended to encompass a computer program accessible from anycomputer-readable device or storage media.

To further improve the analysis and the operation of theplant(s)/system(s), and track environmental and operational trends,smart operations engine can further utilize various machine learningtechniques. Such techniques can optimize the plant operations andperformance, e.g., based on a database of operational data collected(e.g., over several plants), as well as from each specific plant itself.For example, using machine learning techniques, the normal and dynamictrends of plant operations and optimization techniques within the plant,can be determined. Additionally, in certain implementations thedescribed technologies can quickly identify operating parametersdeviating from optimal performance. This information can be leveragedfor preventive maintenance and/or machine and system optimizationimprovements.

As noted above, the described technologies, including smart operationsengine, can be configured to improve the operation and maintenance ofwater treatment and desalination systems. For example, in certainimplementations smart operations engine can automaticallycollect/receive operational and process data from various waterdesalination systems (e.g., from various sensors, components, etc.).Such data can be processed/analyzed (e.g., using machine learning (ML)techniques), and various determinations, etc., can be computed, asdescribed herein.

In certain implementations, various operational parameters can bemeasured at various points at each desalination plant. These parameterscan include flows, pressures, temperatures, analytical parameters (pH,ORP, EC, etc.) and others. In addition, various mechanical andelectrical parameters can be also monitored, e.g., to assess theoperation status of a system (e.g., frequency of various motors, powerconsumption, valve positions etc.). Such data can be transmitted (e.g.,by control system 114 of a particular system) to smart operations enginewhich can also receive/collect data from other connected desalinationplants. Such data can be logged/stored in a database. Additionally,smart operations engine can utilize machine learning and othertechniques to analyze such data and identify trends, anomalies (andtrigger alarms in response), generate preventative maintenanceactivities in response, etc.

The analyzed data can be displayed to users via various user interfaces,e.g., web or mobile interfaces. For example, FIG. 6 depicts an exampleuser interface 602 such as a dashboard that can be provided on variouscomputing devices 508 (PC, tablet, smartphone, etc.) and operatingsystems (Windows, Apple OS etc.). Such a user interface canprovide/present the analyzed data, e.g., for remote viewing by variousoperators, managers, process engineers, etc. (each of which can beprovided different access credentials). This can allow remote assistanceand support for clients, e.g., based on real-time data analysis.

Smart operations engine 504 can communicate (e.g., via secured web linkor other network connections) with various desalination systems/plants506. Monitored data can be received, e.g., from each plant, andcompared, combined, etc. with historic and/or current data from otherplants (e.g., data that went through the ML algorithms analysis). Indoing so real-time feedback on operational data can be generated andprovided. Such analysis can enable ongoing optimization and fine-tuningof system operation and set-points, as described herein. The operationwill be adjusted via controlled elements such as motors VFDs, actuatedvalves and controlled dosing pumps. In doing so, the describedtechnologies can generate and provide real-time feedback, e.g., withrespect to operational changes of one or several systems.

It should be understood that while the described technologies may bedescribed with respect to seawater desalination (e.g., UF and RO-based),this is only by way of example. Accordingly, the described technologiescan also be configured and/or utilized with respect to othertechnologies, such as brackish water desalination and UPW systems (UF,RO, and electrodeionization (EDI)-based), and biological wastewatertreatment systems (membrane aerated biofilm reactors (MABR), moving bedbioreactor (MBBR), Membrane bioreactor (MBR), etc.).

In certain implementations, the described technologies generate alerts(e.g., for maintenance), e.g., upon determining that various datametrics have exceeded defined thresholds. Additionally, in certainimplementations historical data and/or trends can be analyzed (e.g.,using machine learning and artificial intelligence techniques) andutilized to predict/anticipate problems, malfunctions, etc. (and providerelated alerts) before such problem(s) occur (e.g., using machinelearning and artificial intelligence techniques).

Additionally, in certain implementations smart operations engine 504 canbe configured to optimize various operations, e.g., of various plants,systems, facilities, plants, boxes and/or sensors, such as thosedescribed herein. For example, using machine learning techniques,multiple metrics, parameters, etc., can be analyzed, e.g., over a periodof time. In doing so, inefficiencies can be identified and operation ofvarious components, etc., can be adjusted to optimize performance.

As noted above, in certain implementations, the described data can bepresented/depicted to various users via a graphical user interface suchas is depicted in FIG. 6 . It should be understood that various usersmay have different roles and thus different data may be relevant to suchusers. Accordingly, in certain implementations the described interfacecan be customized for one type of user (e.g., a manager) to depict datasuch as site production rate (m3/hr), relative production rate, energyconsumption (kW/hr), product quality, etc. For another user (e.g., aprocess engineer) the described interface can be customized to depict:feed Flow (m3/hr), feed pressure (bar), feed temperature (oC), productflow (m3/hr). In other implementations, various other graphical elementscan be used to depict the data described herein, such as: a feed flowchart, a feed pressure chart, a feed temperature chart, a total productflow chart, a concentrate flow chart, a product connectivity chart, aTMP UF chart, a RO inlet pressure chart, a delta pressure RO chart, arecovery percentage chart, a chemical level percentage chart, and aTimer (e.g., hours and/or lifetime).

Additionally, in certain implementations the described interface cangraphically depict various plants, systems, facilities, etc., e.g., on amap. Various indicators/markers can reflect the state of the plant,system, site, etc. For example, a green marker can reflect that the siteis operating normally/optimally (e.g., no warnings/errors have beendetected), while a yellow marker reflects that warnings are present(e.g., within one of the groups), and a red indicator can reflect a sitewith errors.

In certain implementations, upon selecting such an indicator (e.g., on amap, corresponding a plant, site, system, etc.), the user can bepresented with an overview of the site health status. Additionally,information from various components, sensors, etc., within such a sitecan be collected/updated to depict real-time values.

In certain implementations, a graphical user interface depicting such asite view can include or incorporate data/metrics such as siteproduction rate, relative production rate, energy consumption, productquality, a map of the available groups, and alerts (e.g., an aggregationof all the alerts from various groups).

By integrating the described data and analytics techniques, theoperation of the described plants and systems can be improved andenhanced with additional features. Accurate and site-specific data canbe collected, e.g., regarding precise feed water conditions and seasonalvariations, thereby enabling the operation of each plant in an optimizedmode. Additionally, accurate assessments of the impacts of variable feedconditions, collected over multitudes of plants (and/or historicaldata), on plant operation, can also provide valuable insight for designand optimization of other plants.

By way of illustration, it can be appreciated that each plant may haveits own characteristics, performance curves, etc., that depend on thesystem design and ambient conditions. For example, in certain scenariosa desalination plant is operated at off-design point due to lowercapacity requirement, reduced membrane performance, etc. In such ascenario, smart operations engine 504 can process/analyze data, metrics,etc., from the various components of the plant. In doing so, optimal setpoints for various key parameters can be determined.

For example, smart operations engine 504 can compute variouspretreatment (multi□media filter (MMF) and UF) optimizations tocontinuously improve the pretreatment process, e.g., within adesalination system (such as is described herein). In certainimplementations, both MMF and UF can suffer from instable operation thatmay lead to higher than expected pressure drops (DP or transmembranepressure (TMP)), higher than expected chemical consumption (coagulants,chlorine etc.), and/or lower recovery than expected. In certainscenarios, in order to prevent instable operation, a conservative designand/or conservative operation regimen is typically applied. However,utilizing the described technologies, pretreatment performance can beimproved/optimized. For example, machine learning techniques can performhigh level data analysis and optimize the performance of the system. Forexample chemical consumption of UF can be reduced based on long termdata analysis of TMP vs. chemicals dosage. Additionally,improved/optimized CEB can reduce CIP frequency and increase systemavailability.

By way of further illustration, smart operations engine 504 canprocess/analyze data, metrics, etc., from the various components of theplant (for example, by monitoring the RO feed pressure, membranepressure drop, permeate conductivity, etc.) and improve/optimize variousoperations to lower RO membrane replacement rate. In certainimplementations, the calculated normalized production flow andnormalized salt passage can also be accounted for. In doing so, smartoperations engine 504 can determine, suggest, and/or automatically applylow salinity flushing and/or Cleaning-In-Place procedures. Additionally,using machine learning techniques, smart operations engine 504 canoptimize the flushing and cleanings schedule. As a result of suchoptimization, the appropriate cleaning will be applied on the righttime. In doing so, irreversible fouling or scaling developing on themembrane surface can be reduced. As a result, the overall numbercleanings and the yearly membranes replacement rate can also be reduced.

By way of further illustration, smart operations engine 504 canprocess/analyze data, metrics, etc., to adjust RO and ERD duty points.For example, the operational duty point of the RO may be selected basedon the required production capacity and the design system recovery.However, smart operations engine 504 can detect (e.g., using MLtechniques) operating points with better efficiency and suggest such aduty point adjustment and/or perform such an adjustment automatically(e.g., within predetermined boundaries). For example, data, metrics,etc., such as pump efficiency, ERD efficiency, energy consumption ofdifferent RO units, permeate conductivity, etc. can be accounted for bysmart operations engine 504 in determining an improved duty point.

By way of further illustration, smart operations engine 504 canprocess/analyze data, metrics, etc., to adjust, improve, optimize, etc.,second pass and post-treatment control. In doing so, chemical dosageovershoot for water chemistry balance can be reduced/minimized. Forexample, smart operations engine 504 can be configured to monitor realtime boron rejection as a function of NaOH dosage and optimize NaOHdosage to reach the designated boron rejection without overdosing ofNaOH. Additionally, final pH and Langelier Saturation Index (LSI) can bereached while minimizing NaOH overdosing or CO2 injection.

It can be further appreciated that various plants (e.g., desalinationplants) are designed with safety factors such as production capacity,recovery, chemicals injection, flow rates, and maintenance intervals.However, these safety factors may be implemented based on variousconservative assumptions which may not be necessary (or accurate) in allsettings, contexts, etc. (e.g., with respect to natural seasonalvariance regarding feed conditions). Accordingly, the describedtechnologies can enable real-time automated monitoring of the plant andadjustment of plant conditions. As such, the referenced safety factorscan be accounted for while further improving/optimizing operation of theplant(s) without compromising maintenance and physical integrity of theplant.

Utilizing the described technologies, real-time and detailed informationon a plant's operation and performance, combined with insights drawnfrom machine learning techniques, can enable remote monitoring andtroubleshooting, as well as automatic adjustments. Accordingly, asdescribed herein, the described technologies can provide expertmaintenance support and advice (e.g., via remote monitoring/controlinterfaces), while also detecting malfunctions andrecommending/initiating preventative actions. Predictive maintenancetechniques can be employed to determine the condition of in-serviceequipment to predict when maintenance should be performed. This approachcan enable various efficiencies over routine or time-based preventivemaintenance, because tasks are performed when warranted, whenconveniently scheduled, and under less maintenance cycles and frequency.Predictive maintenance allows convenient scheduling of correctivemaintenance, while preventing unexpected equipment failures. By knowingwhich equipment needs maintenance, maintenance work can be betterplanned (spare parts, people, etc.) and what would have been “unplannedoutages” are transformed to shorter and fewer “planned outages”, thusdecreasing maintenance labor costs and increasing plant availability.The predictive maintenance techniques enabled by the describedtechnologies can considers the actual condition of the equipment, basedon the actual operating environment. This can increase time betweenmaintenance procedures in cases of better conditions than average. Thiscan also reduce system failures, when actual conditions are extreme andmore frequent maintenance is required.

Implementing the described technologies also enables other advantagessuch as increased equipment lifetime, increased plant safety, feweraccidents with negative impact on environment, and optimized spare partshandling.

Many plants are designed with redundant/standby process units or trainsto guarantee performance and capacity under changing circumstances. Thedesign must assume certain conservative down-time for operation andmaintenance (e.g. CIP or maintenance intervals and duration) which maybe inefficient or suboptimal. In contrast, the described technologiescan provide a smart adaptive control system that monitors the system'scondition in real time and provides early fouling detection, allowingshorter and less frequent system shut downs (e.g. for CIP or equipmentmaintenance). In turn this will allow lower redundancy levels andadditional efficiencies.

Systems in which performance is dependent on calibration and tuning,such as desalination plants, can specifically benefit from the describedtechnologies, which can incorporate techniques such as reinforcementlearning. By measuring system inputs such as energy, raw watercondition, chemicals etc. and comparing them to system outcome such asoutput water quality, the described technologies can be trained toincrease its reward (water quality) while tuning the inputs under someboundaries, such that overall efficiency is increased. The advantage ofemploying machine learning results from the fact that system conditionsare constantly changing and such adaptive algorithms can automaticallydynamically determine the operational settings that will yield optimalefficiency.

Additionally, in certain implementations the described technologies cancollect and store the described data (e.g., as received from varioussystems, plants, etc.) in a database (DB) 506. The stored data canreflect, for example, different scenarios, environmental conditions,etc. together with measured operational data under these conditions.Utilizing such data, the described machine learning techniques can beemployed (e.g., to ‘train’ ML models). This enables the trained modelsto be adaptive and optimized on a given site while leveraging knowledgethrough data that are collected from other sites.

In certain implementations, an optimized model can be trained for eachsite and optimized to the specific conditions of that site. The modelcan then be provided/downloaded into the site for distributed operation,such that each site can work independently (e.g., without dependency oncommunication with other devices). This approach also enables easierimplementation of cybersecurity measures which may be important in caseof critical infrastructure such as water.

The described technologies can also be employed to control a cluster ofmodular/package desalination systems that are operating together as asingle plant. For example, multiple containerized seawater desalinationproducts can be combined into mid-size desalination plants of multiplecontainers in parallel. Balancing load and production from each of themodular units, as well as synchronized predictive maintenance and CIPregime of the different systems can be achieved in an optimal mannerusing the described technologies. Such overall smart operation andoptimization will maximize the benefits inherent in a modular plant suchas seasonal capacity changes, redundancy etc.).

It should be understood that the components referenced herein can becombined together or separated into further components, according to aparticular implementation. Additionally, in some implementations,various components of a particular element may be distributed acrossmultiple elements.

It should also be noted that while the technologies described herein areillustrated primarily with respect to water desalination, the describedtechnologies can also be implemented in any number of additional oralternative settings or contexts and towards any number of additionalobjectives.

Certain implementations are described herein as including logic or anumber of components, modules, or mechanisms. Modules can constituteeither software modules (e.g., code embodied on a machine-readablemedium) or hardware modules. A “hardware module” is a tangible unitcapable of performing certain operations and can be configured orarranged in a certain physical manner. In various exampleimplementations, one or more computer systems (e.g., a standalonecomputer system, a client computer system, or a server computer system)or one or more hardware modules of a computer system (e.g., a processoror a group of processors) can be configured by software (e.g., anapplication or application portion) as a hardware module that operatesto perform certain operations as described herein.

In some implementations, a hardware module can be implementedmechanically, electronically, or any suitable combination thereof. Forexample, a hardware module can include dedicated circuitry or logic thatis permanently configured to perform certain operations. For example, ahardware module can be a special-purpose processor, such as aField-Programmable Gate Array (FPGA) or an Application SpecificIntegrated Circuit (ASIC). A hardware module can also includeprogrammable logic or circuitry that is temporarily configured bysoftware to perform certain operations. For example, a hardware modulecan include software executed by a general-purpose processor or otherprogrammable processor. Once configured by such software, hardwaremodules become specific machines (or specific components of a machine)uniquely tailored to perform the configured functions and are no longergeneral-purpose processors. It will be appreciated that the decision toimplement a hardware module mechanically, in dedicated and permanentlyconfigured circuitry, or in temporarily configured circuitry (e.g.,configured by software) can be driven by cost and time considerations.

Accordingly, the phrase “hardware module” should be understood toencompass a tangible entity, be that an entity that is physicallyconstructed, permanently configured (e.g., hardwired), or temporarilyconfigured (e.g., programmed) to operate in a certain manner or toperform certain operations described herein. As used herein,“hardware-implemented module” refers to a hardware module. Consideringimplementations in which hardware modules are temporarily configured(e.g., programmed), each of the hardware modules need not be configuredor instantiated at any one instance in time. For example, where ahardware module comprises a general-purpose processor configured bysoftware to become a special-purpose processor, the general-purposeprocessor can be configured as respectively different special-purposeprocessors (e.g., comprising different hardware modules) at differenttimes. Software accordingly configures a particular processor orprocessors, for example, to constitute a particular hardware module atone instance of time and to constitute a different hardware module at adifferent instance of time.

Hardware modules can provide information to, and receive informationfrom, other hardware modules. Accordingly, the described hardwaremodules can be regarded as being communicatively coupled. Where multiplehardware modules exist contemporaneously, communications can be achievedthrough signal transmission (e.g., over appropriate circuits and buses)between or among two or more of the hardware modules. In implementationsin which multiple hardware modules are configured or instantiated atdifferent times, communications between such hardware modules can beachieved, for example, through the storage and retrieval of informationin memory structures to which the multiple hardware modules have access.For example, one hardware module can perform an operation and store theoutput of that operation in a memory device to which it iscommunicatively coupled. A further hardware module can then, at a latertime, access the memory device to retrieve and process the storedoutput. Hardware modules can also initiate communications with input oroutput devices, and can operate on a resource (e.g., a collection ofinformation).

The various operations of example methods described herein can beperformed, at least partially, by one or more processors that aretemporarily configured (e.g., by software) or permanently configured toperform the relevant operations. Whether temporarily or permanentlyconfigured, such processors can constitute processor-implemented modulesthat operate to perform one or more operations or functions describedherein. As used herein, “processor-implemented module” refers to ahardware module implemented using one or more processors.

Similarly, the methods described herein can be at least partiallyprocessor-implemented, with a particular processor or processors beingan example of hardware. For example, at least some of the operations ofa method can be performed by one or more processors orprocessor-implemented modules. Moreover, the one or more processors canalso operate to support performance of the relevant operations in a“cloud computing” environment or as a “software as a service” (SaaS).For example, at least some of the operations can be performed by a groupof computers (as examples of machines including processors), with theseoperations being accessible via a network (e.g., the Internet) and viaone or more appropriate interfaces (e.g., an API).

The performance of certain of the operations can be distributed amongthe processors, not only residing within a single machine, but deployedacross a number of machines. In some example implementations, theprocessors or processor-implemented modules can be located in a singlegeographic location (e.g., within a home environment, an officeenvironment, or a server farm). In other example implementations, theprocessors or processor-implemented modules can be distributed across anumber of geographic locations.

The modules, methods, applications, and so forth described inconjunction with FIGS. 1-5 are implemented in some implementations inthe context of a machine and an associated software architecture. Thesections below describe representative software architecture(s) andmachine (e.g., hardware) architecture(s) that are suitable for use withthe disclosed implementations.

Software architectures are used in conjunction with hardwarearchitectures to create devices and machines tailored to particularpurposes. For example, a particular hardware architecture coupled with aparticular software architecture will create a mobile device, such as amobile phone, tablet device, or so forth. A slightly different hardwareand software architecture can yield a smart device for use in the“internet of things,” while yet another combination produces a servercomputer for use within a cloud computing architecture. Not allcombinations of such software and hardware architectures are presentedhere, as those of skill in the art can readily understand how toimplement the inventive subject matter in different contexts from thedisclosure contained herein.

FIG. 7 is a block diagram illustrating components of a machine 700,according to some example implementations, able to read instructionsfrom a machine-readable medium (e.g., a machine-readable storage medium)and perform any one or more of the methodologies discussed herein.Specifically, FIG. 7 shows a diagrammatic representation of the machine700 in the example form of a computer system, within which instructions716 (e.g., software, a program, an application, an applet, an app, orother executable code) for causing the machine 700 to perform any one ormore of the methodologies discussed herein can be executed. Theinstructions 716 transform the general, non-programmed machine into aparticular machine programmed to carry out the described and illustratedfunctions in the manner described. In alternative implementations, themachine 700 operates as a standalone device or can be coupled (e.g.,networked) to other machines. In a networked deployment, the machine 700can operate in the capacity of a server machine or a client machine in aserver-client network environment, or as a peer machine in apeer-to-peer (or distributed) network environment. The machine 700 cancomprise, but not be limited to, a server computer, a client computer,PC, a tablet computer, a laptop computer, a netbook, a set-top box(STB), a personal digital assistant (PDA), an entertainment mediasystem, a cellular telephone, a smart phone, a mobile device, a wearabledevice (e.g., a smart watch), a smart home device (e.g., a smartappliance), other smart devices, a web appliance, a network router, anetwork switch, a network bridge, or any machine capable of executingthe instructions 716, sequentially or otherwise, that specify actions tobe taken by the machine 700. Further, while only a single machine 700 isillustrated, the term “machine” shall also be taken to include acollection of machines 700 that individually or jointly execute theinstructions 716 to perform any one or more of the methodologiesdiscussed herein.

The machine 700 can include processors 710, memory/storage 730, and I/Ocomponents 750, which can be configured to communicate with each othersuch as via a bus 702. In an example implementation, the processors 710(e.g., a Central Processing Unit (CPU), a Reduced Instruction SetComputing (RISC) processor, a Complex Instruction Set Computing (CISC)processor, a Graphics Processing Unit (GPU), a Digital Signal Processor(DSP), an ASIC, a Radio-Frequency Integrated Circuit (RFIC), anotherprocessor, or any suitable combination thereof) can include, forexample, a processor 712 and a processor 714 that can execute theinstructions 716. The term “processor” is intended to include multi-coreprocessors that can comprise two or more independent processors(sometimes referred to as “cores”) that can execute instructionscontemporaneously. Although FIG. 7 shows multiple processors 710, themachine 700 can include a single processor with a single core, a singleprocessor with multiple cores (e.g., a multi-core processor), multipleprocessors with a single core, multiple processors with multiples cores,or any combination thereof.

The memory/storage 730 can include a memory 732, such as a main memory,or other memory storage, and a storage unit 736, both accessible to theprocessors 710 such as via the bus 702. The storage unit 736 and memory732 store the instructions 716 embodying any one or more of themethodologies or functions described herein. The instructions 716 canalso reside, completely or partially, within the memory 732, within thestorage unit 736, within at least one of the processors 710 (e.g.,within the processor's cache memory), or any suitable combinationthereof, during execution thereof by the machine 700. Accordingly, thememory 732, the storage unit 736, and the memory of the processors 710are examples of machine-readable media.

As used herein, “machine-readable medium” means a device able to storeinstructions (e.g., instructions 716) and data temporarily orpermanently and can include, but is not limited to, random-access memory(RAM), read-only memory (ROM), buffer memory, flash memory, opticalmedia, magnetic media, cache memory, other types of storage (e.g.,Erasable Programmable Read-Only Memory (EEPROM)), and/or any suitablecombination thereof. The term “machine-readable medium” should be takento include a single medium or multiple media (e.g., a centralized ordistributed database, or associated caches and servers) able to storethe instructions 716. The term “machine-readable medium” shall also betaken to include any medium, or combination of multiple media, that iscapable of storing instructions (e.g., instructions 716) for executionby a machine (e.g., machine 700), such that the instructions, whenexecuted by one or more processors of the machine (e.g., processors710), cause the machine to perform any one or more of the methodologiesdescribed herein. Accordingly, a “machine-readable medium” refers to asingle storage apparatus or device, as well as “cloud-based” storagesystems or storage networks that include multiple storage apparatus ordevices. The term “machine-readable medium” excludes signals per se.

The I/O components 750 can include a wide variety of components toreceive input, provide output, produce output, transmit information,exchange information, capture measurements, and so on. The specific I/Ocomponents 750 that are included in a particular machine will depend onthe type of machine. For example, portable machines such as mobilephones will likely include a touch input device or other such inputmechanisms, while a headless server machine will likely not include sucha touch input device. It will be appreciated that the I/O components 750can include many other components that are not shown in FIG. 7 . The I/Ocomponents 750 are grouped according to functionality merely forsimplifying the following discussion and the grouping is in no waylimiting. In various example implementations, the I/O components 750 caninclude output components 752 and input components 754. The outputcomponents 752 can include visual components (e.g., a display such as aplasma display panel (PDP), a light emitting diode (LED) display, aliquid crystal display (LCD), a projector, or a cathode ray tube (CRT)),acoustic components (e.g., speakers), haptic components (e.g., avibratory motor, resistance mechanisms), other signal generators, and soforth. The input components 754 can include alphanumeric inputcomponents (e.g., a keyboard, a touch screen configured to receivealphanumeric input, a photo-optical keyboard, or other alphanumericinput components), point based input components (e.g., a mouse, atouchpad, a trackball, a joystick, a motion sensor, or another pointinginstrument), tactile input components (e.g., a physical button, a touchscreen that provides location and/or force of touches or touch gestures,or other tactile input components), audio input components (e.g., amicrophone), and the like.

In further example implementations, the I/O components 750 can includebiometric components 756, motion components 758, environmentalcomponents 760, or position components 762, among a wide array of othercomponents. For example, the biometric components 756 can includecomponents to detect expressions (e.g., hand expressions, facialexpressions, vocal expressions, body gestures, or eye tracking), measurebiosignals (e.g., blood pressure, heart rate, body temperature,perspiration, or brain waves), identify a person (e.g., voiceidentification, retinal identification, facial identification,fingerprint identification, or electroencephalogram basedidentification), and the like. The motion components 758 can includeacceleration sensor components (e.g., accelerometer), gravitation sensorcomponents, rotation sensor components (e.g., gyroscope), and so forth.The environmental components 760 can include, for example, illuminationsensor components (e.g., photometer), temperature sensor components(e.g., one or more thermometers that detect ambient temperature),humidity sensor components, pressure sensor components (e.g.,barometer), acoustic sensor components (e.g., one or more microphonesthat detect background noise), proximity sensor components (e.g.,infrared sensors that detect nearby objects), gas sensors (e.g., gasdetection sensors to detect concentrations of hazardous gases for safetyor to measure pollutants in the atmosphere), or other components thatcan provide indications, measurements, or signals corresponding to asurrounding physical environment. The position components 762 caninclude location sensor components (e.g., a Global Position System (GPS)receiver component), altitude sensor components (e.g., altimeters orbarometers that detect air pressure from which altitude can be derived),orientation sensor components (e.g., magnetometers), and the like.

Communication can be implemented using a wide variety of technologies.The I/O components 750 can include communication components 764 operableto couple the machine 700 to a network 780 or devices 770 via a coupling782 and a coupling 772, respectively. For example, the communicationcomponents 764 can include a network interface component or othersuitable device to interface with the network 780. In further examples,the communication components 764 can include wired communicationcomponents, wireless communication components, cellular communicationcomponents, Near Field Communication (NFC) components, Bluetooth®components (e.g., Bluetooth® Low Energy), Wi-Fi® components, and othercommunication components to provide communication via other modalities.The devices 770 can be another machine or any of a wide variety ofperipheral devices (e.g., a peripheral device coupled via a USB).

Moreover, the communication components 764 can detect identifiers orinclude components operable to detect identifiers. For example, thecommunication components 764 can include Radio Frequency Identification(RFID) tag reader components, NFC smart tag detection components,optical reader components (e.g., an optical sensor to detectone-dimensional bar codes such as Universal Product Code (UPC) bar code,multi-dimensional bar codes such as Quick Response (QR) code, Azteccode, Data Matrix, Dataglyph, MaxiCode, PDF417, Ultra Code, UCC RSS-2Dbar code, and other optical codes), or acoustic detection components(e.g., microphones to identify tagged audio signals). In addition, avariety of information can be derived via the communication components764, such as location via Internet Protocol (IP) geolocation, locationvia Wi-Fi® signal triangulation, location via detecting an NFC beaconsignal that can indicate a particular location, and so forth.

In various example implementations, one or more portions of the network780 can be an ad hoc network, an intranet, an extranet, a virtualprivate network (VPN), a local area network (LAN), a wireless LAN(WLAN), a WAN, a wireless WAN (WWAN), a metropolitan area network (MAN),the Internet, a portion of the Internet, a portion of the PublicSwitched Telephone Network (PSTN), a plain old telephone service (POTS)network, a cellular telephone network, a wireless network, a Wi-Fi®network, another type of network, or a combination of two or more suchnetworks. For example, the network 780 or a portion of the network 780can include a wireless or cellular network and the coupling 782 can be aCode Division Multiple Access (CDMA) connection, a Global System forMobile communications (GSM) connection, or another type of cellular orwireless coupling. In this example, the coupling 782 can implement anyof a variety of types of data transfer technology, such as SingleCarrier Radio Transmission Technology (1×RTT), Evolution-Data Optimized(EVDO) technology, General Packet Radio Service (GPRS) technology,Enhanced Data rates for GSM Evolution (EDGE) technology, thirdGeneration Partnership Project (3GPP) including 3G, fourth generationwireless (4G) networks, Universal Mobile Telecommunications System(UMTS), High Speed Packet Access (HSPA), Worldwide Interoperability forMicrowave Access (WiMAX), Long Term Evolution (LTE) standard, othersdefined by various standard-setting organizations, other long rangeprotocols, or other data transfer technology.

The instructions 716 can be transmitted or received over the network 780using a transmission medium via a network interface device (e.g., anetwork interface component included in the communication components764) and utilizing any one of a number of well-known transfer protocols(e.g., HTTP). Similarly, the instructions 716 can be transmitted orreceived using a transmission medium via the coupling 772 (e.g., apeer-to-peer coupling) to the devices 770. The term “transmissionmedium” shall be taken to include any intangible medium that is capableof storing, encoding, or carrying the instructions 716 for execution bythe machine 700, and includes digital or analog communications signalsor other intangible media to facilitate communication of such software.

Throughout this specification, plural instances can implementcomponents, operations, or structures described as a single instance.Although individual operations of one or more methods are illustratedand described as separate operations, one or more of the individualoperations can be performed concurrently, and nothing requires that theoperations be performed in the order illustrated. Structures andfunctionality presented as separate components in example configurationscan be implemented as a combined structure or component. Similarly,structures and functionality presented as a single component can beimplemented as separate components. These and other variations,modifications, additions, and improvements fall within the scope of thesubject matter herein.

Although an overview of the inventive subject matter has been describedwith reference to specific example implementations, variousmodifications and changes can be made to these implementations withoutdeparting from the broader scope of implementations of the presentdisclosure. Such implementations of the inventive subject matter can bereferred to herein, individually or collectively, by the term“invention” merely for convenience and without intending to voluntarilylimit the scope of this application to any single disclosure orinventive concept if more than one is, in fact, disclosed.

The implementations illustrated herein are described in sufficientdetail to enable those skilled in the art to practice the teachingsdisclosed. Other implementations can be used and derived therefrom, suchthat structural and logical substitutions and changes can be madewithout departing from the scope of this disclosure. The DetailedDescription, therefore, is not to be taken in a limiting sense, and thescope of various implementations is defined only by the appended claims,along with the full range of equivalents to which such claims areentitled.

As used herein, the term “or” can be construed in either an inclusive orexclusive sense. Moreover, plural instances can be provided forresources, operations, or structures described herein as a singleinstance. Additionally, boundaries between various resources,operations, modules, engines, and data stores are somewhat arbitrary,and particular operations are illustrated in a context of specificillustrative configurations. Other allocations of functionality areenvisioned and can fall within a scope of various implementations of thepresent disclosure. In general, structures and functionality presentedas separate resources in the example configurations can be implementedas a combined structure or resource. Similarly, structures andfunctionality presented as a single resource can be implemented asseparate resources. These and other variations, modifications,additions, and improvements fall within a scope of implementations ofthe present disclosure as represented by the appended claims. Thespecification and drawings are, accordingly, to be regarded in anillustrative rather than a restrictive sense.

What is claimed is:
 1. A method comprising: passing water through areverse osmosis process; backwashing a first set of ultrafiltrationmembranes or a second set of ultrafiltration membranes with brinegenerated by the reverse osmosis process; and backwashing at least oneof the first set of ultrafiltration membranes or the second set ofultrafiltration membranes with one or more chemicals and reverse osmosispermeate, wherein the brine generated from the reverse osmosis processis directly communicated, through an energy recovery device, to abackwash inlet of a backwashing system of the first set ofultrafiltration membranes.
 2. A method for water desalinationcomprising: backwashing one or more ultrafiltration membranes with brinegenerated by a reverse osmosis process; backwashing one or moreultrafiltration membranes with one or more chemicals and reverse osmosispermeate water; and operating a plurality of ultrafiltration trains inparallel to one another.
 3. The method of claim 1, wherein passing waterthrough a reverse osmosis process further comprises passing the waterthrough one or more filters.
 4. The method of claim 3, wherein the oneor more filters comprise one or more disc filters.
 5. The method ofclaim 3, wherein the one or more filters are cleaned during an automatedcleaning cycle.
 6. The method of claim 5, wherein, during the automatedcleaning cycle, the one or more filters are decompressed, rinsed, andrecompressed.
 7. The method of claim 1, wherein the first set ofultrafiltration membranes and the second set of ultrafiltrationmembranes are configured to filter water that is provided to one or morereverse osmosis membranes that perform the reverse osmosis process. 8.The method of claim 7, wherein the brine is received via a feed from theone or more reverse osmosis membranes.
 9. The method of claim 1, whereinbackwashing a first set of ultrafiltration membranes or a second set ofultrafiltration membranes comprises treating the first set ofultrafiltration membranes with the brine generated by the reverseosmosis process while the second set of ultrafiltration membranesfilters water.
 10. The method of claim 1, wherein backwashing at leastone of the first set of ultrafiltration membranes or the second set ofultrafiltration membranes comprises treating the first set ofultrafiltration membranes with the one or more chemicals and the reverseosmosis permeate water while the second set of ultrafiltration membranesfilters water.
 11. The method of claim 1, further comprising performinga rinsing operation upon determining that a reverse osmosis process hasstopped for a defined period of time.
 12. The method of claim 1, whereinsaid first set of ultrafiltration membranes and the second set ofultrafiltration membranes operate in parallel.
 13. The method of claim1, comprising periodically backwashing the first set of ultrafiltrationmembranes.
 14. The method of claim 1, comprising continuous operatingsaid reverse osmosis process.
 15. The method of claim 1, fordesalinating water.